Effective Scheduling for Coded Distributed Storage in Wireless Sensor Networks

A distributed storage approach is proposed to access data reliably and to cope with node failures in wireless sensor networks. This approach is based on random linear network coding in combination with a scheduling algorithm based on backpressure. Upper bounds are provided on the maximum rate at which data can be reliably stored. Moreover, it is shown that the backpressure algorithm allows to operate the network in a decentralized fashion for any rate below this maximum

Dynamic algorithms for multicast with intra-session network coding

The problem of multiple multicast sessions with intra-session network coding in time-varying networks is considered. The network-layer capacity region of input rates that can be stably supported is established. Dynamic algorithms for multicast routing, network coding, power allocation, session scheduling, and rate allocation across correlated sources, which achieve stability for rates within the capacity region, are presented. This work builds on the back-pressure approach introduced by Tassiulas et al., extending it to network coding and correlated sources. In the proposed algorithms, decisions on routing, network coding, and scheduling between different sessions at a node are made locally at each node based on virtual queues for different sinks. For correlated sources, the sinks locally determine and control transmission rates across the sources. The proposed approach yields a completely distributed algorithm for wired networks. In the wireless case, power control among different transmitters is centralized while routing, network coding, and scheduling between different sessions at a given node are distributed

An Adaptive Fault-Tolerant Communication Scheme for Body Sensor Networks

A high degree of reliability for critical data transmission is required in body sensor networks (BSNs). However, BSNs are usually vulnerable to channel impairments due to body fading effect and RF interference, which may potentially cause data transmission to be unreliable. In this paper, an adaptive and flexible fault-tolerant communication scheme for BSNs, namely AFTCS, is proposed. AFTCS adopts a channel bandwidth reservation strategy to provide reliable data transmission when channel impairments occur. In order to fulfill the reliability requirements of critical sensors, fault-tolerant priority and queue are employed to adaptively adjust the channel bandwidth allocation. Simulation results show that AFTCS can alleviate the effect of channel impairments, while yielding lower packet loss rate and latency for critical sensors at runtime.Comment: 10 figures, 19 page

Optimization driven multi-hop network design and experimentation: the approach of the FP7 project OPNEX

International audienceThe OPNEX project exemplifies system and optimization theory as the foundations for algorithms that provably maximize capacity of wireless networks. The algorithms termed in abstract network models have been converted to protocols and architectures practically applicable to wireless systems. A validation methodology through experimental protocol evaluation in real network testbeds has been proposed and used. OPNEX uses recent advances in system theoretic network control, including the Back-Pressure principle, max-weight scheduling, utility optimization, congestion control, and the primal-dual method for extracting network algorithms. These approaches exhibited vast potential for achieving high capacity and full exploitation of resources in abstract network models and found their way to reality in high performance architectures developed as a result of the research conducted within OPNEX